Nsidered an outlier if either x-Q99 > 1.1IQ, or Q1-x > 1.1IQ, i.e. x is

Nsidered an outlier if either x-Q99 > 1.1IQ, or Q1-x > 1.1IQ, i.e. x is outside the interval between Q1 and Q99 at a distance higher than 10 of such interval. The incomplete data are those lacking required CpGs in the window around a genomic site to infer the DNA methylation level. We then sorted all data points according to the third dimension into a particular number of binsSharifi-Zarchi et al. BMC Genomics (2017) 18:Page 19 of(identified as function argument) to produce equalwidth bins in the whole range of the 3rd dimension. Data points of each bin were subsequently assigned the same color of the whole spectrum. The data points were interpolated with a triangle-based linear method and projected them onto a 3-dimensional surface to ensure that the visual representation was not biased to the points overlaying other points. The scatter plots representing H3K4me1, H3K4me3 and DNA methylation in different cell types were produced by this method.Peak intersection analysis between WT and KO cellsDNA methylation; MEF: Mouse embryonic fibroblast; NCBI: National Center for Biotechnology Information; P4hb: Prolyl 4-hydroxylase subunit ; Pawr: Pro-apoptotic WT1 regulator; Pkm: Muscle pyruvate kinase; Pol2: RNA polymerase 2; Ppp4c: Protein phosphatase 4, catalytic subunit; RNA-seq: RNA sequencing; RRBS: Reduced Representation Bisulfite Sequencing; PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/28494239 SINE: Short Interspersed Nuclear Element; TAB-seq: Tet-assisted bisulfite sequencing; Tcf19: Transcription factor 19; Tet1: The epigenetic regulators tet methylcytosine dioxygenase 1; TF: Transcription factor; TSS: Transcription Start Site; TTS: Transcription Termination Site; WCE: Whole cell extract; WGBS: Whole-Genome Bisulfite Sequencing; WT: Wild type Acknowledgments We thank Farzane Emami for creating the artwork of the scientific concept. Data analysis was performed using JNJ-54781532 site computing cluster facilities of the Institute for Research in Fundamental Sciences, Tehran, and of the Biodonostia Health Research Institute, San Sebastian. Funding DG and MJ A-B. have been supported by grants DFG10/15, DFG15/15 and DFG141/16 from Diputaci Foral de Gipuzkoa, Spain, Ministry of Economy and Competitiveness, Spain, MINECO grants PI16/01430 and BFU 2016?798P and funds from IKERBASQUE, Basque Foundation for Science, Spain. Also, this study was funded by grants from Royan Institute, the Iran National Science Foundation (INSF), and Iran Science Elites Federation to HB. Availability of data and materials All data used in this work is publicly available and described in Table 1. Authors’ contributions AS-Z, MS, and MJA-B designed the project. KA, MT, RJT, DG, and HRS provided biological insights and checked the results. HP and DG contributed to the statistical analysis. AS-Z performed the computational analysis. HC checked the plots. HB and MS supervised the project. AS-Z, DG and MJA-B wrote the manuscript. All authors have read and approved the manuscript. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests.Cross-normalization of processed ChIP-seq data was performed with the MAnorm software [77]. The same software was used to identify the common and specific peaks for pairs of cell types (WT versus KO). A peak was called specific to one cell type if the normalized enrichment value had more than a 2-fold change between the two cell types with a p-value <1e-5. Transcriptional activity on each pe.